Structural health monitoring has been studied by a number of researchers as well as various industries to keep up with the increasing demand for preventive maintenance routines. This work presents a novel method for reconstruct prompt, informed strain/stress responses at the hot spots of the structures based on strain measurements at remote locations. The structural responses measured from usage monitoring system at available locations are decomposed into modal responses using empirical mode decomposition. Transformation equations based on finite element modeling are derived to extrapolate the modal responses from the measured locations to critical locations where direct sensor measurements are not available. Then, two numerical examples (a two-span beam and a 19956-degree of freedom simplified airfoil) are used to demonstrate the overall reconstruction method. Finally, the present work investigates the effectiveness and accuracy of the method through a set of experiments conducted on an aluminium alloy cantilever beam commonly used in air vehicle and spacecraft. The experiments collect the vibration strain signals of the beam via optical fiber sensors. Reconstruction results are compared with theoretical solutions and a detailed error analysis is also provided.
Details
- Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation
- He, Jingjing (Author)
- Zhou, Yibin (Author)
- Guan, Xuefei (Author)
- Zhang, Wei (Author)
- Zhang, Weifang (Author)
- Liu, Yongming (Author)
- Ira A. Fulton Schools of Engineering (Contributor)
-
Digital object identifier: 10.3390/s16081290
-
Identifier TypeInternational standard serial numberIdentifier Value1424-8220
Citation and reuse
Cite this item
This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.
He, J., Zhou, Y., Guan, X., Zhang, W., Zhang, W., & Liu, Y. (2016). Time Domain Strain/Stress Reconstruction Based on Empirical Mode Decomposition: Numerical Study and Experimental Validation. Sensors, 16(8), 1290. doi:10.3390/s16081290